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Solve linear, integer, and knapsack optimization problems through a simple JSON interface.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Opti-MCP" yet — see the docs or source repo.
Use Opti-MCP to build a linear programming model: products A and B have profits 30 and 50; machine hours are limited to 40 with usage 2 and 4; raw material is limited to 30 with usage 3 and 2. Maximize profit and return the optimal quantities and total profit.
Returns the solved model with optimal quantities for A and B, maximum profit, and constraint feasibility.
Use Opti-MCP to solve an integer program: 3 employees cover morning and evening shifts. Employee 1 can work both shifts, cost 8; employee 2 only morning, cost 5; employee 3 only evening, cost 6. Morning needs at least 2 workers and evening needs at least 2. Variables are binary, and the goal is to minimize total cost.
Provides the optimal assignment for each employee, minimum total cost, and whether a feasible solution exists.
Use Opti-MCP to solve a 0/1 knapsack problem: budget limit 15, with 5 projects whose costs are 4, 6, 3, 5, and 8, and values are 7, 10, 4, 8, and 13. Each project can be selected at most once. Maximize total value and return chosen project IDs, total cost, and total value.
Returns the optimal set of selected projects, along with total cost, total value, and optimality status.
Access COPT docs, sample code, and citations to use solver APIs accurately.
Find minimal variable fixes that make equations valid from noisy OCR data.
Let AI manage OmniFocus tasks, projects, and inbox workflows on macOS.
Build, debug, and manage software tasks with natural language across LLMs.
Lets AI present choices and collect user selections through an interactive interface.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.